Intelligent Automation has been misused widely and is a fairly ambiguous term and possibly another buzzword. A few things are wrong with it. What kind of intelligence should it represent? Who supplies the intelligence? Does intelligent mean learning simple decisions? Learning rules or learning whole processes? What should it automate? People? Backend interactions? An add on to RPA? In complex environments (a.k.a. daily business interactions) machine learning has to be setup and pointed to well-behaved data sets. You need not only process experts and now data modeling expert but also ML experts. Bigger and more complex project to fail! Or invent a completely different kind of learning ...

I feel that in orthodox BPM systems ML has little to do and the business little to gain. We have had the User-Trained Agent for a long-time but customers did want it at most as a Best Next Action recommendation. We could train it to recognize whole processes, but it is difficult to learn decision thresholds from observing work. I guess the main issue is that the people involved in it do 'process thinking' and leaving anything undefined up to a machine to learn goes against the grain.

Diagrams constrain and hinder the process dynamics as it is incredibly complex to express typical business rules in a logic tree. If BPM does not enforce compliance, why bother? Intelligence can be applied once the whole paradigm of BPM is changed. And if that does not happen inside it will happen outside BPM.

First, if we are talking about AI and 'learning' processes then we are dealing with a market that is still in its infancy. 2019 will be an important year to expand the footprint and learn how to leverage 'learning' and deploy in more parts of the business particularly in the customer touchpoints. However several factors- maturity of organizations, platforms, tools, implementation capabilities, approaches etc. - need to be ironed out for it to scale and play a big role thus the acceleration of AI and 'learning' processes to me are a few years away. There is just too many embedded platforms and organizational baggage to swing on a dime in 2019. Otherwise, the general term of intelligent automation, implying processes that are automated and have encapsulated business capabilities, is far and away past the tipping point. There are loads of intelligent automation processes imbedded in organizations that can processes without humans and cover many user scenarios thus prewired 'decisioning' drives the outcomes. But that means the processes have been wired for specific scenarios and decisions vs a process that 'learns' and changes on the fly. But we are near for true 'learning' intelligent automation.

As Max, Stuart and Bogdan so rightfully state: AI, ML, Intelligent Automation are terms typically misused to hype up otherwise "boring" BPM topics and basically generate more sales for large consultants (such as Deloitte and the likes) or to justify yet another AI/ML start up.

My main concern with these concepts has everything to do with the fact that it only talks about the HOW and not the WHAT and WHY. Companies define their strategies based on the WHY (why are we in business, why are selling this product or service?) and these strategies are then translated into the WHAT (typically done by the management level in the company). Finally and ultimately we arrive at the HOW and this is were a lot of artificial, intelligent and automation things come in. The basically replace a number of human tasks, and that is good and I believe there will be a huge market potential for these kind of tools and concepts.

What I am missing in almost all articles on these topics is simply the link to the WHAT and the WHY and the former one being typically expressed in the form of end to end processes. Also the Deloitte article does not speak about the tie-in from the intelligent automation perspective into the business processes (which are the main core structure in the company). Until they (developers and manufacturers of AI, ML, IA etc) realize that all they do needs to support one or more business processes, it will remain a niche market in my opinion and as a result, their role will be rather marginal in 2019. Once they do realize this, their role will be much and much bigger.

Automation with complex and not-transparent decision making (done by ML or AI or ….) may lead to rather brittle digital systems. As usual, instead of talking about yet another magic technology which will solve all (and some more) our problems, it is necessary to think about creating viable and dependable systems.

Intelligent automation will have many aspects to help business but will need that transparency in exactly what and how is being automated and of course seamlessly integrated into the end to end business process? Such IA in 2019 may well see the wide spread creation of custom applications at a click of a button based upon the specific business user needs thru adoption of no code enterprise level software. This should open the door for many simple and practical automation opportunities for operational business processes to support users helping to improve productivity and user experiences.